R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> x <- c(425.25,417.75,410.25,395.25,546.75,539.25,425.25,349.50,357.00,357.00,364.50,380.25,334.50,288.75,251.25,251.25,395.25,410.25,296.25,167.25,235.50,235.50,288.75,319.50,312.00,235.50,273.75,258.75,387.75,357.00,235.50,144.75,228.00,251.25,273.75,303.75,243.00,190.50,213.00,220.50,417.75,417.75,303.75,288.75,334.50,312.00,372.75,448.50,463.50,357.00,327.00,296.25,501.75,516.75,478.50,516.75,509.25,448.50,516.75,592.50,623.25,531.75,471.00,516.75,714.00,774.75,759.75,789.75,782.25,706.50,835.50,866.25,911.25,774.75,721.50,782.25,927.00,1056.00,1025.25,1025.25,1040.25,987.75,1124.25,1124.25,1101.00,972.00,995.25,1010.25,1109.25,1238.25,1146.75,1192.50,1154.25,1131.75,1306.50,1268.25,1215.00,1139.25,1215.00,1253.25,1299.00,1359.75,1299.00,1336.50,1290.75,1283.25,1473.00,1488.75,1428.00,1321.50,1412.25,1450.50,1496.25,1564.50,1496.25,1549.50,1526.25,1443.00,1617.75,1617.75)
> par1 = '12'
> par1 <- '12'
> #'GNU S' R Code compiled by R2WASP v. 1.2.291 ()
> #Author: root
> #To cite this work: Wessa P. (2012), Standard Deviation-Mean Plot (v1.0.6) in Free Statistics Software (v$_version), Office for Research Development and Education, URL http://www.wessa.net/rwasp_smp.wasp/
> #Source of accompanying publication: Office for Research, Development, and Education
> #
> par1 <- as.numeric(par1)
> (n <- length(x))
[1] 120
> (np <- floor(n / par1))
[1] 10
> arr <- array(NA,dim=c(par1,np))
> j <- 0
> k <- 1
> for (i in 1:(np*par1))
+ {
+ j = j + 1
+ arr[j,k] <- x[i]
+ if (j == par1) {
+ j = 0
+ k=k+1
+ }
+ }
> arr
        [,1]   [,2]   [,3]   [,4]   [,5]   [,6]    [,7]    [,8]    [,9]   [,10]
 [1,] 425.25 334.50 312.00 243.00 463.50 623.25  911.25 1101.00 1215.00 1428.00
 [2,] 417.75 288.75 235.50 190.50 357.00 531.75  774.75  972.00 1139.25 1321.50
 [3,] 410.25 251.25 273.75 213.00 327.00 471.00  721.50  995.25 1215.00 1412.25
 [4,] 395.25 251.25 258.75 220.50 296.25 516.75  782.25 1010.25 1253.25 1450.50
 [5,] 546.75 395.25 387.75 417.75 501.75 714.00  927.00 1109.25 1299.00 1496.25
 [6,] 539.25 410.25 357.00 417.75 516.75 774.75 1056.00 1238.25 1359.75 1564.50
 [7,] 425.25 296.25 235.50 303.75 478.50 759.75 1025.25 1146.75 1299.00 1496.25
 [8,] 349.50 167.25 144.75 288.75 516.75 789.75 1025.25 1192.50 1336.50 1549.50
 [9,] 357.00 235.50 228.00 334.50 509.25 782.25 1040.25 1154.25 1290.75 1526.25
[10,] 357.00 235.50 251.25 312.00 448.50 706.50  987.75 1131.75 1283.25 1443.00
[11,] 364.50 288.75 273.75 372.75 516.75 835.50 1124.25 1306.50 1473.00 1617.75
[12,] 380.25 319.50 303.75 448.50 592.50 866.25 1124.25 1268.25 1488.75 1617.75
> arr.mean <- array(NA,dim=np)
> arr.sd <- array(NA,dim=np)
> arr.range <- array(NA,dim=np)
> for (j in 1:np)
+ {
+ arr.mean[j] <- mean(arr[,j],na.rm=TRUE)
+ arr.sd[j] <- sd(arr[,j],na.rm=TRUE)
+ arr.range[j] <- max(arr[,j],na.rm=TRUE) - min(arr[,j],na.rm=TRUE)
+ }
> arr.mean
 [1]  414.0000  289.5000  271.8125  313.5625  460.3750  697.6250  958.3125
 [8] 1135.5000 1304.3750 1493.6250
> arr.sd
 [1]  66.18878  69.04445  63.70102  87.11070  88.92473 131.55290 136.55623
 [8] 106.65642 101.38694  87.91302
> arr.range
 [1] 197.25 243.00 243.00 258.00 296.25 395.25 402.75 334.50 349.50 296.25
> (lm1 <- lm(arr.sd~arr.mean))

Call:
lm(formula = arr.sd ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
   73.94838      0.02719  

> (lnlm1 <- lm(log(arr.sd)~log(arr.mean)))

Call:
lm(formula = log(arr.sd) ~ log(arr.mean))

Coefficients:
  (Intercept)  log(arr.mean)  
       2.7935         0.2677  

> (lm2 <- lm(arr.range~arr.mean))

Call:
lm(formula = arr.range ~ arr.mean)

Coefficients:
(Intercept)     arr.mean  
  238.32553      0.08619  

> postscript(file="/var/wessaorg/rcomp/tmp/1s8641471029683.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.sd,main='Standard Deviation-Mean Plot',xlab='mean',ylab='standard deviation')
> dev.off()
null device 
          1 
> postscript(file="/var/wessaorg/rcomp/tmp/2397p1471029683.ps",horizontal=F,onefile=F,pagecentre=F,paper="special",width=8.3333333333333,height=5.5555555555556) 
> plot(arr.mean,arr.range,main='Range-Mean Plot',xlab='mean',ylab='range')
> dev.off()
null device 
          1 
> 
> #Note: the /var/wessaorg/rcomp/createtable file can be downloaded at http://www.wessa.net/cretab
> load(file="/var/wessaorg/rcomp/createtable")
> 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Standard Deviation-Mean Plot',4,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Section',header=TRUE)
> a<-table.element(a,'Mean',header=TRUE)
> a<-table.element(a,'Standard Deviation',header=TRUE)
> a<-table.element(a,'Range',header=TRUE)
> a<-table.row.end(a)
> for (j in 1:np) {
+ a<-table.row.start(a)
+ a<-table.element(a,j,header=TRUE)
+ a<-table.element(a,arr.mean[j])
+ a<-table.element(a,arr.sd[j] )
+ a<-table.element(a,arr.range[j] )
+ a<-table.row.end(a)
+ }
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/3xukt1471029683.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: S.E.(k) = alpha + beta * Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/4nwai1471029683.tab") 
> a<-table.start()
> a<-table.row.start(a)
> a<-table.element(a,'Regression: ln S.E.(k) = alpha + beta * ln Mean(k)',2,TRUE)
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'alpha',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[1]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'beta',header=TRUE)
> a<-table.element(a,lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'S.D.',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,2])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'T-STAT',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,3])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'p-value',header=TRUE)
> a<-table.element(a,summary(lnlm1)$coefficients[2,4])
> a<-table.row.end(a)
> a<-table.row.start(a)
> a<-table.element(a,'Lambda',header=TRUE)
> a<-table.element(a,1-lnlm1$coefficients[[2]])
> a<-table.row.end(a)
> a<-table.end(a)
> table.save(a,file="/var/wessaorg/rcomp/tmp/5u5ir1471029683.tab") 
> 
> try(system("convert tmp/1s8641471029683.ps tmp/1s8641471029683.png",intern=TRUE))
character(0)
> try(system("convert tmp/2397p1471029683.ps tmp/2397p1471029683.png",intern=TRUE))
character(0)
> 
> 
> proc.time()
   user  system elapsed 
  0.902   0.078   0.992